In the realm of power system analysis and management, the identification and mitigation of network weak unbalance issues are of paramount importance. This paper introduces a novel method for addressing symbolic network weak unbalance using evolutionary algorithms. The proposed approach leverages the power of genetic algorithms to optimize network configurations, reducing weak unbalance and enhancing overall system stability. Through rigorous experimentation and validation, the method showcases its efficacy in improving power system performance, minimizing voltage deviations, and increasing operational robustness.